Nonparametric models of Convergence

The assessment of convergence process through nonparametric models reveals much better understanding of convergence than the above models. Kernel distribution plots clearly evident that in 1981, there is no evidence of existence of any convergence clubs.

The distribution was more or less with a single peak. However, with greater pace of fertility transition from the year, 1991, emergence of a secondary peak was evident and such secondary peaks were more clearly apparent from the year 2001 and 2011. Such process clearly manifests that though, fertility transition is universal in India, but still there are unequal rate of progress across the states. The states with TFR below the national average are forming a different convergent clubs and rest of the states is forming other secondary peaks. A separate assessment of such process for rural and urban areas separately reveals that the process is more pronounced in case of rural than urban areas. Since 1991, the emergence of multiple peaks is observed in rural areas and clearly apparent in the years 2001 and 2011. However, in urban areas, the presence of secondary peaks is clearly evident only in the 2011 (Figure 6.11, 6.12, 6.13).

-27.892

-13.197

-2.078

-30 -25 -20 -15 -10 -5 0

1981-91 1991-2001 2001-09

Rate of relative converegence (in %)

Period

Rate of relative converegence (in %)

152 Figure 6.11. Kernel density estimates of Total Fertility Rate distribution in India and major states, 1981-2011

Figure 6.12. Kernel density estimates of Total Fertility Rate distribution in Rural areas of India and major states, 1981-2011

0.1.2.3.4

2 3 4 5 6

kernel = epanechnikov, bandwidth = .45 1981

0.1.2.3.4

Density

1 2 3 4 5 6

kernel = epanechnikov, bandwidth = .48 1991

.1.2.3.4.5

1 2 3 4 5

kernel = epanechnikov, bandwidth = .45 2001

.1.2.3.4.5.6

Density

1.5 2 2.5 3 3.5 4

kernel = epanechnikov, bandwidth = .34 2011

0.1.2.3.4

2 3 4 5 6 7

kernel = epanechnikov, bandwidth = .47 1981

0.1.2.3.4

Density

1 2 3 4 5 6

kernel = epanechnikov, bandwidth = .5 1991

.1.2.3.4

1 2 3 4 5

kernel = epanechnikov, bandwidth = .49 2001

.1.2.3.4.5.6

Density

1.5 2 2.5 3 3.5 4

kernel = epanechnikov, bandwidth = .36 2011

153 Figure 6.13. Kernel density estimates of Total Fertility Rate distribution in urban areas of India and major states, 1981-2011

6.5. Discussion

This chapter is a comprehensive assessment of fertility convergence hypotheses in India over the geographic units (states) and socioeconomic spectrum. I have tested with both conventional and contemporary metrics of convergence for total fertility rates for Indian states and socioeconomic strata. From a theoretical context, this chapter makes a critical contribution to advancing knowledge on patterns of the progress in fertility transition. The key theoretical and analytical contributions of this chapter are as follow:

 An innovative framework has been conceptualised to understand the integrated process of fertility transition and fertility convergence, alongside socioeconomic and health transition. This framework serves as an important tool to describe the critical stages and pathways of fertility convergence across the Indian states.

 The fertility transition plots and Change-points, analyses indicate a varying pattern of fertility transition across the major Indian states. Critical change-points in fertility rates across the states indicate a substantially varying pattern.

While few of the states have experienced major fertility changes as early as in

0.1.2.3.4.5

2 3 4 5

kernel = epanechnikov, bandwidth = .37 1981

.1.2.3.4.5

Density

1.5 2 2.5 3 3.5 4

kernel = epanechnikov, bandwidth = .34 1991

0.2.4.6.8

1.5 2 2.5 3 3.5

kernel = epanechnikov, bandwidth = .27 2001

.2.4.6.8 1

Density

1 1.5 2 2.5 3

kernel = epanechnikov, bandwidth = .19 2011

154 the 1970s, other states have experienced significant changes in fertility as late as the 2000s. This process has created a condition of differentials of steady state and catching-up process where, the states with higher fertility rates experienced a greater fall in fertility rates thus, catching-up with the states of lower fertility rates.

 The β-convergence model estimates suggested that due to pronounced fertility divergence during the early phase of 1981-1991, the estimates for an overall period (1981-2009) showed fertility divergence. The initial phase of divergence in TFR among the states was mainly because of the relatively greater decline in TFR of the demographically advanced (mostly comprising south Indian states) states compared with the demographically lagging states (mostly comprising north Indian states). However, due to greater fertility decline in the states with higher fertility rates in post 1990s period, the divergence in fertility was replaced with convergence in fertility. Sigma convergence estimates revealed the similar pattern: initially showed divergence then catching-up with the fertility convergence process.

 The results of inequality based convergence measures indicated the convergence in absolute and relative dispersion in fertility rates across the 15 major states with varying time trends. The convergence estimates for absolute dispersion of fertility rates were consistent with absolute β-convergence estimates: divergence in the pre-1990 period was replaced with convergence in fertility in the post-1990 period. However, the convergence estimates in the relative dispersion of fertility rates showed persistent divergence, but with a substantial decline in the volume of divergence for the recent period. This suggests that convergence in the absolute dispersion of fertility rates may not always give a guarantee of relative convergence. Because, the initiation of these two processes may not occur at the same point. This pattern implies that convergence in average fertility rates and absolute dispersion of between state fertility rates are necessary, but not a sufficient condition for relative convergence. Therefore, the convergence estimates should follow both absolute and relative distributions of any population parameters such as fertility.

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 The test of non-parametric model of convergence showed the evidence for emergence of convergence clubs with acceleration in fertility transition for the recent periods (post-1990s) rather convergence as whole.

Overall, this chapter has advanced considerable knowledge in measuring the progress of fertility transition in the Indian states using a range of convergence models both in terms of efficacy and equity across the states and socioeconomic spectrum. The assessment of India and state level fertility transition demonstrates evidence of transformation from progressive transition disequilibrium to progressive transition equilibrium phase. Moreover, based on the results of both standard and innovative metrics of convergence, this study concludes that the earlier phase of divergence in fertility rates across the 15 major states of India was being replaced by emerging convergence in fertility rates for the recent period, but the progress is not resulted into absolute convergence yet. The trends and patterns suggest the strong prospects of continued fertility convergence among the Indian states if the club of higher fertility states will further move to catch the club of lower fertility states.

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CHAPTER 7